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Conference Paper: A truthful (1-epsilon)-optimal mechanism for on-demand cloud resource provisioning

TitleA truthful (1-epsilon)-optimal mechanism for on-demand cloud resource provisioning
Other TitlesA truthful (1-ɛ)-optimal mechanism for on-demand cloud resource provisioning
Authors
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001779
Citation
The 2015 IEEE Conference on Computer Communications Workshops (INFOCOM Wksps), Hong Kong, 26 April-1 May 2015. In Conference Proceedings, 2015, p. 1-9 How to Cite?
AbstractOn-demand resource provisioning in cloud computing provides tailor-made resource packages (typically in the form of VMs) to meet users’ demands. Public clouds nowadays provide more and more elaborated types of VMs, but have yet to offer the most flexible dynamic VM assembly, which is partly due to the lack of a mature mechanism for pricing tailor-made VMs on the spot. This work proposes an efficient randomized auction mechanism based on a novel application of smoothed analysis and randomized reduction, for dynamic VM provisioning and pricing in geo-distributed cloud data centers. This auction, to the best of our knowledge, is the first one in literature that achieves (i) truthfulness in expectation, (ii) polynomial running time in expectation, and (iii) (1-ɛ)-optimal social welfare in expectation for resource allocation, where ɛ can be arbitrarily close to 0. Our mechanism consists of three modules: (1) an exact algorithm to solve the NP-hard social welfare maximization problem, which runs in polynomial time in expectation, (2) a perturbation-based randomized resource allocation scheme which produces a VM provisioning solution that is (1-ɛ)-optimal and (3) an auction mechanism that applies the perturbation-based scheme for dynamic VM provisioning and prices the customized VMs using a randomized VCG payment, with a guarantee in truthfulness in expectation. We validate the efficacy of the mechanism through careful theoretical analysis and trace-driven simulations.
Persistent Identifierhttp://hdl.handle.net/10722/213546

 

DC FieldValueLanguage
dc.contributor.authorZhang, X-
dc.contributor.authorWu, C-
dc.contributor.authorLi, Z-
dc.contributor.authorLau, FCM-
dc.date.accessioned2015-08-05T04:17:51Z-
dc.date.available2015-08-05T04:17:51Z-
dc.date.issued2015-
dc.identifier.citationThe 2015 IEEE Conference on Computer Communications Workshops (INFOCOM Wksps), Hong Kong, 26 April-1 May 2015. In Conference Proceedings, 2015, p. 1-9-
dc.identifier.urihttp://hdl.handle.net/10722/213546-
dc.description.abstractOn-demand resource provisioning in cloud computing provides tailor-made resource packages (typically in the form of VMs) to meet users’ demands. Public clouds nowadays provide more and more elaborated types of VMs, but have yet to offer the most flexible dynamic VM assembly, which is partly due to the lack of a mature mechanism for pricing tailor-made VMs on the spot. This work proposes an efficient randomized auction mechanism based on a novel application of smoothed analysis and randomized reduction, for dynamic VM provisioning and pricing in geo-distributed cloud data centers. This auction, to the best of our knowledge, is the first one in literature that achieves (i) truthfulness in expectation, (ii) polynomial running time in expectation, and (iii) (1-ɛ)-optimal social welfare in expectation for resource allocation, where ɛ can be arbitrarily close to 0. Our mechanism consists of three modules: (1) an exact algorithm to solve the NP-hard social welfare maximization problem, which runs in polynomial time in expectation, (2) a perturbation-based randomized resource allocation scheme which produces a VM provisioning solution that is (1-ɛ)-optimal and (3) an auction mechanism that applies the perturbation-based scheme for dynamic VM provisioning and prices the customized VMs using a randomized VCG payment, with a guarantee in truthfulness in expectation. We validate the efficacy of the mechanism through careful theoretical analysis and trace-driven simulations.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001779-
dc.relation.ispartofIEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)-
dc.rightsIEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleA truthful (1-epsilon)-optimal mechanism for on-demand cloud resource provisioning-
dc.title.alternativeA truthful (1-ɛ)-optimal mechanism for on-demand cloud resource provisioning-
dc.typeConference_Paper-
dc.identifier.emailWu, C: cwu@cs.hku.hk-
dc.identifier.emailLau, FCM: fcmlau@cs.hku.hk-
dc.identifier.authorityWu, C=rp01397-
dc.identifier.authorityLau, FCM=rp00221-
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros246573-
dc.identifier.spage1-
dc.identifier.epage9-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 150805-

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